code: def testKerasIntegerLookup(self):
      if not tf.executing_eagerly():
          self.skipTest("This test is TF2 only.")
  
      key = "feature_key"
      vocab_list = [2, 3, 4]
  
      keras_input = tf.keras.Input(
          shape=(1,), name=key, dtype=tf.dtypes.int32
      )
      id_input = tf.keras.layers.IntegerLookup(
          vocabulary=vocab_list,
          num_oov_indices=0,
          output_mode="multi_hot",
      )
  
      state_input = [3, 2, 2, 4, 3]
      state = {key: tf.expand_dims(state_input, -1)}
      input_spec = {key: tensor_spec.TensorSpec([1], tf.int32)}
  
      network = encoding_network.EncodingNetwork(
          input_spec,
          preprocessing_combiner=tf.keras.Sequential(
              [keras_input, id_input]
          ),
      )
  
      output, _ = network(state)
      expected_shape = (len(state_input), len(vocab_list))
      self.assertEqual(expected_shape, output.shape)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.networks import encoding_network
  from tf_agents.specs import tensor_spec
  from tf_agents.utils import test_utils
label_desc: Use image node_id 14 for calling the EncodingNetworkTest obj's underlying member method code with example usage: obj.testKerasIntegerLookup() without return types